The aim of this article is to detect high frequency (HF) features in a noisy signal. We propose a parametric characterization in the Fourier domain of the HF features. Then we introduce a procedure to evaluate these parameters and compute a p-value which assesses in a quantitative manner the presence or absence of such features, that we also call "...
This work is motivated by the analysis of ecological interaction networks. Poisson stochastic blockmodels are widely used in this field to decipher the structure that underlies a weighted network, while accounting for covariate effects. Efficient algorithms based on variational approximations exist for frequentist inference, but without statistical...
Our project represents a contribution to the so-called hostile site management solution such as historic ruins, oil pipelines, earthquake-affected buildings, unexploited mines, sewage pipelines, sites infected by radioactivity. These places have a significant characteristic, the difficulty of access, which makes human intervention very expensive an...
Motivated by an application to the clustering of milking kinetics of dairy goats, we propose in this paper a novel approach for functional data clustering. This issue is of growing interest in precision livestock farming that has been largely based on the development of data acquisition automation and on the development of interpretative tools to c...
This work proposes an original method for disease subtyping from both longitudinal clinical variables and genetic markers via a mixture of regressions model, with logistic weights function of a potentially large number of genetic variables. In order to address these large-scale problems, variable selection is an essential step. We thus propose to d...
These tips provide a quick and concentrated guide for beginners in the analysis of network data.
In a wide variety of situations, anomalies in the behaviour of a complex system, whose health is monitored through the observation of a random vector X = (X1,. .. , X d) valued in R d , correspond to the simultaneous occurrence of extreme values for certain subgroups α ⊂ {1,. .. , d} of variables Xj. Under the heavy-tail assumption, which is precis...
In a wide variety of situations, anomalies in the behaviour of a complex system, whose health is monitored through the observation of a random vector X = (X1,. .. , X d) valued in R d , correspond to the simultaneous occurrence of extreme values for certain subgroups α ⊂ {1,. .. , d} of variables Xj. Under the heavy-tail assumption, which is precis...
This paper develops a new global optimisation method that applies to a family of criteria that are not entirely known. This family includes the criteria obtained from the class of posteriors that have nor-malising constants that are analytically not tractable. The procedure applies to posterior probability densities that are continuously differen-t...
This paper develops a new global optimisation method that applies to a family of criteria that are not entirely known. This family includes the criteria obtained from the class of posteriors that have nor-malising constants that are analytically not tractable. The procedure applies to posterior probability densities that are continuously differen-t...
